The strawberry industry presently uses manual labor to sort several hundred million plants every year into good and bad categories, a tedious and costly step in the process of bringing fruit to market. Plants raised by nursery farms are cultivated in large fields grown like grass. The plants are harvested at night in the fall and winter when they are dormant and can be moved to their final locations for berry production. During the nursery farm harvest, the quality of the plants coming from the field is highly variable. Only about half of the harvested plants are of sufficient quality to be sold to the berry farms. It is these plants that ultimately yield the berries seen in supermarkets and road-side fruit stands. The present invention provides new sorting technologies that will fill a valuable role by standardizing plant quality and reducing the amount of time that plants are out of the ground between the nursery farms and berry farms.
Present operations to sort plants are done completely manually with hundreds of migrant workers. A typical farm employs 500-1000 laborers for a 6-8 week period each year during the plant harvest. The present invention is novel both in its application of advanced computer vision to the automated plant-sorting task, and in the specific design of the computer vision algorithms. One embodiment of the present invention applies to strawberry nursery farms. However, there are other embodiments of the software engine being for many different types of plants that require sophisticated quality sorting.